Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron-Reference-Cited by-同舟云学术

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Achieving DFT accuracy with a machine-learning interatomic potential: Thermomechanics and defects in bcc ferromagnetic iron

Published:2018-01-30 Issue:1 Volume:2 Page:
ISSN:2475-9953
Container-title:Physical Review Materials
language:en
Short-container-title:Phys. Rev. Materials

Author:

Dragoni Daniele,Daff Thomas D.,Csányi Gábor,Marzari Nicola

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Engineering and Physical Sciences Research Council

Publisher

American Physical Society (APS)

Subject

Physics and Astronomy (miscellaneous),General Materials Science

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevMaterials.2.013808/fulltext

Reference99 articles.

1. Ultrasoft pseudopotentials applied to magnetic Fe, Co, and Ni: From atoms to solids

2. The melting curve of iron at the pressures of the Earth's core from ab initio calculations

3. Ab initiophonon dispersions of Fe and Ni

4. Physics of Iron at Earth's Core Conditions

5. Harmonic and anharmonic properties of Fe and Ni: Thermal expansion, exchange-correlation errors, and magnetism

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